Instructions to use north/t5_base_NCC_lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use north/t5_base_NCC_lm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("north/t5_base_NCC_lm") model = AutoModelForSeq2SeqLM.from_pretrained("north/t5_base_NCC_lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from north/t5_base_NCC_lm: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/north/t5_base_NCC_lm/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://north/t5_base_NCC_lm/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/north/t5_base_NCC_lm/resolve/main/flax_model.msgpack
2.33 GB
- Xet hash:
- 059120a99934eae6766bafe7d5f61d04e80d9133ccd77add61a1a27c49093ca4
- Size of remote file:
- 2.33 GB
- SHA256:
- d54fccc328632e8c95a4e31d3919568dc930d6698651200345a2ed9ccae6eb6a
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